Personalization of a website depends on gathering data about a specific user. The data typically comes in three forms, explicit, implicit and transactional data. Explicit data includes data such as the user indicating choices on a particular subject. Explicit data also includes data that traces and records the website that the user visits. Generally, explicit data reflects specific user choices, while implicit data attempts to infer the user's likes and dislikes from the user's actions.
On the Internet, consumer behavior may be predicted using both explicit and implicit information to deliver a more individualized experience to the user. Personalization falls into two broad categories, rule-based and collaborative. A rule-based system utilizes generally understood patterns of behavior to propose appropriate matches. For example, in an on-line merchandising application, this might take the form of offering a selection of products, to someone purchasing a related product. The collaborative approach is a tool that discovers correlations in large bodies of data to predict likely affinities or choices.
Various methods and systems for customizing consumer needs for products and services have been proposed. In an exemplary disclosure, U.S. Pat. No. 6,141,666 to Tobin discloses a server-based communication system that provides dynamic customization of hypertext tagged documents presented to clients accessing the system. The customization pertains to the content of the documents based on specific requirements of a class to which the clients belong to. This class may be defined by an entity of the source, which refers the client to the system. The system utilizes a database, that dynamically retrieves stored data in response to the server software tool, which configures the data into hypertext tagged documents. The system utilizes a dynamic token scheme to pass the identity of the referring network site from document to document to eventually identify documents accessed by the client through the hypertext tags.
U.S. Pat. No. 6,128,663 to Thomas discloses improved techniques for customizing information collected from a content server through a network to a user of a computer system. The information is customized in accordance with demographic classifications, user interests or preferences. The customization process may involve advertising using banners targeted to the user. The customization can also involve altering portions of a web page to be displayed to the user so that the web page is more effective or desirable for the user. In addition to customization of the information to be displayed to the user, the invention also provides techniques for obtaining demographic information about the user of the computer system, such that the demographic information may be transferred to the content provider such that the content provider would have knowledge about the user.
U.S. Pat. No. 6,115,709 to Gilmour et al. discloses a method of constructing a user knowledge profile. The method includes distinct public and private portions with different access restrictions and assignment of confidence level to content within an electronic document. The document is associated with a user such as, for example, the author of the document. The content may be potentially indicative of the knowledge base of the user. The content is then stored in either the public or private portion of the user knowledge profile, dependent upon whether the confidence level exceeds or falls below a predetermined threshold level. The public portion of the user knowledge profile is freely accessible by third parties, while the private portion is placed under restricted access.
U.S. Pat. No. 6,247,031 B1 to Bernardo et al. discloses an automated system for approving website content. The system includes software with prestored templates comprising html formatting code, text fields and formulas. A user is directed to select features and options desired for the website. Further, based on these selections, the tool prompts the user to supply data to populate fields of the templates determined by the tool to correspond to the selected features and options.
U.S. Pat. No. 6,209,007 B1 to Kelley et al. discloses a web internet screen customizing system, specifically, a process for creating a customized web page containing information from other web pages that is accessible by client computer from an inner or internet site is disclosed.
U.S. Pat. No. 6,167,441 to Himmel discloses a customization of web pages based on requestor type. Specifically, customized internet content is provided by requesting client device using an intercepting agent based on the capabilities of the requesting client. The agent typically at the web server to which the client requests is directed intercepts a request made by a requesting client device for a file from the web server. The agent detects client device capability information about the requesting client device, such as display or memory capabilities. The client request is redirected to a uniform resource locator (URL) according to the detected client device capability information to retrieve a version of the requested file.
U.S. Pat. No. 6,289,244 B1 to Conly et al. discloses a self-audit system for use in managing and monitoring measurements acquired by an implantable medical device in a period of time. The self-audit system includes programming one or more valid ranges for one or more measurements acquired in an implantable medical device, acquiring one or measurements in an implantable medical device and comparing the one or more measurements to their associated valid ranges. The information is recorded if it is not within its associated valid range, and displaying a warning message if a measurement is not within the associated valid range.
U.S. Pat. No. 6,063,028 to Luciano discloses an automated treatment selection method. Specifically, a method for facilitating choosing a treatment or treatment regime and for predicting the outcome of a treatment for it is ordered, which is diagnosed and monitored or other appropriately trained and licensed professional based upon the symptoms experienced by a patient. In a preferred embodiment, one method for predicting patient response includes performing at least one measurement of a symptom on a patient and measuring that symptom to derive a baseline patient profile. A set of a plurality of predictor variables defines the data of the baseline patient profile wherein the set of predictor variables includes predictive symptoms and a set of treatment options. Further, the invention enables to derive a model that represents the relationship between patient response and the set of predictor variables. The model is then implemented to predict the response of the patient to a treatment.
The above-described methods, apparatus and process are implemented using preferably keystrokes or a mouse and standard interface with a web browser to access a website. The website may consist of back-end data or modules, such as educational modules, links to other websites, historical data, or any kind of other source of back-end data. Generally, the user may access documents, video and audio feedbacks and links to other websites. Further, using these tools, a user may interact with a site that is sufficiently intelligent to select the right information tailored to the interests of the user.
Some websites include personalization engines built into them which look at specific interactions that a person is having and look at the keystrokes or the mouse strokes or any other explicit data that is coming in. Based on those explicit interactions, the system may be able to pull up certain background data that is specific to the person. For example, the person may elect to see an educational module and the personalization engine will search for the information and present it to the browser. Although personalization engines are used to identify consumer preferences, patients with implanted devices have highly specialized needs as it relates to device data. Current personalization engines do not appear to serve those needs.
Accordingly, there is a need for a personalization engine that is responsive to data collected from implanted medical devices (IMDs), including peripheral or external devices in communication with IMDs such that information relating to the performance of the IMD, delivered therapy information, as well diagnostic information could be presented in a manner that is tailored to the needs, concerns and interests of the patient.